A transition towards sustainable engineering materials is vital in reducing the environmental footprint of contemporary infrastructure and manufacturing activities. The present research delves into sustainable material usage, examining key parameters such as cost-effectiveness, availability, durability, recyclability, and environmental footprint. Alternatives such as recycled metals, bamboo, natural fibre composites, and bioplastics are promising alternatives to traditional …

Reducing Environmental Impact Through Sustainable Engineering MaterialsRead More

Using sustainable materials in engineering can decrease the impacts caused by climate change, pollution, and resource depletion. The study highlights how innovations such as bamboo, hempcrete, and bioplastics offer environmentally responsible alternatives to conventional materials by examining renewable, recycled, and biodegradable materials. The article is entirely based on secondary sources, including journals, articles, academic books, …

Minimizing Ecological Footprint with Eco-Friendly Engineering MaterialsRead More

Both resource usage and greenhouse gas emission problems are significant problems worldwide, and these problems emphasize the need for engineering materials for environmental sustainability. The research uses case studies and Life Cycle Assessment (LCA) to select alternative materials such as geopolymer concrete, hempcrete, recycled metals, bamboo, engineered wood and bioplastics.

The convergence of edge computing and federated learning (FL) offers promising solutions for privacy-preserving machine learning in Internet of Things (IoT) environments. However, integrating these technologies raises complex challenges in terms of security, communication efficiency, and heterogeneous device capabilities. This survey explores the landscape of secure federated learning techniques tailored for edge-IoT settings, with a …

Secure Federated Learning in Edge-IoT Environments: A Survey on Privacy-Preserving Techniques and System ChallengesRead More

This review examines low-power techniques critical for the implementation of Micro Electromechanical Systems (MEMS)-based shock and vibration sensing systems in remote, long-term monitoring applications. The primary aim is to identify, assess, and compare strategies for reducing power consumption in sensor interfaces, signal conditioning, microcontroller units, wireless communication, and energy harvesting systems. The scope includes ultra-low-power …

Low-Power Methodologies for MEMS-Based Shock and Vibration Sensors in Remote Monitoring – A ReviewRead More